Velma Amondi: The Future of AI Belongs to Organisations That Rethink How They Work

Artificial intelligence has moved beyond experimentation. Across industries, boardrooms are shifting their focus from whether to adopt AI to how to deploy it at scale while delivering measurable business value. Yet many organisations remain trapped in pilot projects, struggling to bridge the gap between ambition and execution. In this interview with CIO Africa, Velma Amondi, Country and Technology Leader at IBM East Africa, discusses why trusted data and governance are becoming as important as AI models, how IBM’s watsonx platform is helping enterprises operationalise AI, the evolving role of the CIO, and why the next phase of AI transformation will be defined by redesigned operating models rather than technology alone.

Q: Tell us about your journey to becoming IBM’s East Africa Manager. What experiences have shaped your leadership philosophy?

A: When I reflect on my journey to becoming IBM’s Country and Technology Leader for East Africa, one word comes to mind: adaptability.

I did not follow a carefully mapped-out career path. In fact, many of the opportunities that shaped my career came through evolving business priorities and roles I had never planned for. Each time, I chose to lean into the change rather than resist it. Looking back, those moments became the greatest catalysts for my growth.

I began my career in technical roles, solving problems through technology. As my career evolved, I found myself leading partner ecosystems, commercial teams and business strategy across increasingly diverse markets. Every transition expanded my perspective. It taught me that while technology is important, lasting transformation begins with people. Technology enables change, but people make it happen. That realisation has shaped my leadership philosophy.

Many people assume leadership is about having all the answers. My experience has taught me something different. Leadership is about creating an environment where people can thrive, contribute their strengths and succeed together. Some of the most rewarding moments in my career have come from seeing individuals grow into opportunities they never imagined for themselves. That is the kind of leader I strive to be.

Leading across East Africa has reinforced another important lesson. Every market is different. Every customer faces unique opportunities and challenges. There is rarely a single answer that works everywhere. It has taught me to listen first, stay curious and bring together different perspectives before making decisions. Collaboration is not simply a leadership style for me. It is how better decisions are made and how sustainable outcomes are achieved.

If there is one lesson my journey has taught me, it is that careers are rarely linear. Often, the opportunities that shape us most are the ones we never saw coming. For me, remaining adaptable, continuously learning and investing in people have been the defining themes of my career. They continue to guide how I lead today and how I hope to contribute to the future of technology leadership in Africa.

Q: Many organisations still describe themselves as being in the “pilot stage.” What separates companies that successfully move AI into production from those that remain stuck in proof-of-concept mode?

A: The organisations that are creating real business value from AI are the ones that start with a business challenge, not a technology experiment. Rather than asking where they can use AI, they ask where AI can help improve customer experience, increase productivity, reduce costs, or accelerate growth.

Moving from pilot to production also requires a strong foundation. That means having access to trusted data, establishing clear governance, and ensuring accountability across the organisation. Many AI initiatives stall because organisations underestimate the effort required to integrate AI into existing workflows and operational processes.

Leadership commitment is another critical factor. AI transformation cannot be owned by the technology team alone. The organisations seeing the greatest success are those where business leaders, technology leaders and operations teams are aligned around measurable outcomes.

What we’re increasingly seeing is that scaling AI isn’t just about deploying models—it’s about adopting an AI operating model. That means redesigning how work gets done, embedding AI into everyday workflows, and enabling people and AI agents to work together across functions. Organisations that simply layer AI onto existing processes often struggle to move beyond pilots. Those that rethink workflows, decision-making and governance are the ones realizing measurable business value.

Recent IBM Institute for Business Value research highlights the challenge. While nearly 80% of executives expect AI to contribute significantly to revenue by 2030, only 24% say they have a clear understanding of where that revenue will come from. Closing that gap between ambition and execution is what distinguishes organisations that scale successfully from those that remain in the pilot stage.

Q: AI conversations increasingly start in the boardroom rather than the IT department. What has driven this shift?

A: AI is no longer viewed as a technology initiative; it is increasingly seen as a business transformation opportunity. IBM Institute for Business Value research found that 85% of CEOs believe every executive leader will need a deeper level of technology expertise in their own domain. That reflects a broader shift where technology decisions are becoming business decisions, and AI is at the center of that transformation.

Boards and executive teams recognise that AI has the potential to influence nearly every aspect of the enterprise, from productivity and customer engagement to innovation and competitive advantage. As a result, discussions have moved beyond infrastructure and technical implementation to focus on business strategy, operating models, workforce readiness and value creation.

At the same time, there is growing recognition that AI brings new responsibilities around governance, security, compliance and risk management. These are issues that require executive oversight and board-level engagement.

We’re also seeing leadership teams ask a different question. The conversation is shifting from “Where can we use AI?” to “How do we operate as an AI-enabled business?” That means rethinking operating models, governance, talent and business processes, not simply deploying new technology. Those are strategic decisions, which is why AI has firmly moved into the boardroom.

Q: IBM has invested heavily in enterprise AI through watsonx. How is the platform helping organisations move from experimentation to production?

A: Many organisations understand the potential of AI, but scaling it across an enterprise presents a very different set of challenges. Enterprises operate in complex environments with multiple data sources, existing applications, regulatory requirements and security considerations. Moving AI into production requires a platform that addresses those realities.

watsonx was designed to help organisations move AI from experimentation to enterprise-wide adoption. It provides the capabilities to build, deploy and govern AI, prepare and manage enterprise data, and apply governance throughout the AI lifecycle, helping organisations scale AI responsibly, and securely.

A major challenge for many companies is moving beyond isolated use cases. Organisations often have successful pilots in individual business units, but struggle to replicate that success across the enterprise. watsonx provides a framework that enables AI to be deployed consistently and managed at scale.

It also helps organisations address issues such as compliance, security, transparency and governance, all of which become increasingly important as AI moves into mission-critical business processes.

We’re applying the same principles inside IBM as our own Client Zero. IBM Bob, our enterprise AI-powered software engineering platform, is now used by more than 100,000 IBM employees worldwide, with surveyed users reporting an average 45% productivity gain across software development tasks. Those experiences help us understand firsthand what it takes to operationalize AI responsibly and at scale. Not just deploy AI models, but embed them into the way work gets done every day.

Q: As AI agents and autonomous systems become more capable, how do you see the role of the CIO evolving?

A: The role of the CIO is evolving from technology operator to enterprise transformation leader.

As organisations deploy more AI-powered systems and agents, CIOs will play an increasingly important role in ensuring these systems are built on trusted data, governed responsibly and aligned with business priorities. Success will depend not only on deploying technology, but on creating an environment where AI can be adopted confidently and at scale.

The CIO of the future will spend less time managing infrastructure and more time orchestrating outcomes across the enterprise. They will need to bring together data, AI, automation and human expertise to create more intelligent and efficient business processes.

Another important responsibility will be workforce transformation. As AI changes how work is performed, CIOs will help organisations rethink workflows, develop new skills and enable employees to work effectively alongside AI systems.

Ultimately, the most successful CIOs will be those who can connect technology strategy with business strategy. Their value will increasingly be measured by the outcomes they deliver—whether that’s driving innovation, improving productivity, accelerating growth or strengthening resilience.

Q: Looking ahead three to five years, how do you expect AI to reshape businesses?

A: Over the next three to five years, AI will become increasingly embedded into the core operations of organisations. Rather than existing as standalone applications, AI will be integrated into business processes, customer interactions and decision-making workflows.

We are likely to see broader adoption of AI assistants and AI agents that can automate routine activities, streamline workflows and help employees focus on more strategic and higher-value work. The greatest impact won’t come from the technology itself, but from how organisations redesign their operating models so people and AI work together seamlessly.

AI will also enable organisations to derive greater value from their data. Leaders will be able to access insights faster, make decisions more confidently and respond to changing market conditions with greater agility.

At the same time, successful adoption will require more than technology. Organisations will need to invest in workforce skills, change management and governance to ensure AI is deployed responsibly and effectively.

IBM’s own experience reinforces this. By embedding AI across our business as Client Zero, IBM has delivered more than $4.5 billion in productivity gains, demonstrating that the greatest value comes when AI is integrated into core business operations rather than deployed as isolated use cases.

According to IBM Institute for Business Value research, organisations expect AI-driven productivity gains to exceed 40 per cent by 2030. The businesses that benefit most will be those that combine AI with trusted data, strong governance and a clear focus on business outcomes.

In the end, AI will not simply change how organisations use technology. It will reshape how work gets done, how businesses operate and how value is created across the enterprise.